ฝึกพูดภาษาอังกฤษด้วยเทคนิค Shadowing จากวิดีโอ: "AI Existential Risk" Was Invented to Distract Us
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162 ประโยค
หากประโยคสั้นหรือยาวเกินไป กดที่ Edit เพื่อปรับแก้
1
So you might have seen this week
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that a charming young man named Jacob Coxon gave the entire
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world a panic attack by quitting his job at the AI company Anthropic
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and saying that he was quitting because he was worried that Anthropic's work could lead to the extinction of humanity.
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And he tweeted that everybody else building AI earnestly believes this.
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Now, the media called him a whistleblower for saying this, but I think that's kind of a weird thing to call him
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when a colleague of his immediately quote tweeted him and said, Jacob is correct, we really do earnestly believe that AI could kill all humans.
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In fact, we think there's a 10% chance within the next decade.
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And then the CEO of the company wrote an entire fucking op-ed saying the exact same thing
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and that we needed to slow down AI development in order to prevent this.
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Oh, and let's not forget that Elon Musk has been saying this shit for the better part of the last decade.
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So how can you be a whistleblower when everybody in your industry not only agrees with you, they also are openly saying the thing you're saying all the time?
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Like, you're not a whistleblower if you quit the hip-hop industry and say, Hey, I'm kind of worried some of those guys are selling drugs.
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Anyway, this has led to, simply put, a culture-wide freakout, where literally everyone in the media,
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in social media, just people who come up to me at the coffee shop and grab me by the lapels is asking, like, is it really gonna happen?
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Is AI really gonna kill all of us?
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Like, people are really afraid about this and they want an answer.
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And I think we need to acknowledge, first of all, this is not an answerable question.
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It's actually designed to be an unanswerable question.
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Like, just the statement, you know, there's a 10% chance that humanity will become extinct in the next decade.
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How would you go about calculating such a thing or even refuting it?
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Like, I can make any argument I want about what LLMs can do and someone can make a counterargument.
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No one is going to be convinced, right?
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But I think there is something more interesting going on in the Jacob Coxon story because it's that phrase,
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everyone at Anthropic believes that AI is an existential risk.
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Everyone in the AI industry believes that that is true.
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Because think about this, every organization, right, has to instill some kind of beliefs among its members in order to do the work it does, right?
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I mean, everybody at Goldman Sachs believes the free market is great, capitalism is the best system, and that they are the wealth creators who deserve big bonuses.
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Everyone in the Mormon Church believes they should all tithe 10% of their income
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and that they each get a special planet when they die.
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And everyone who worked at Philip Morris in the 80s believed
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that cigarettes tasted great and did not cause any of that nasty cancer.
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You know, there's that Upton Sinclair quote, It's difficult to get a man to understand something when a salary depends on his not understanding it.
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While the opposite is also true.
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It's guaranteed that someone will believe something if their salary depends on them believing it.
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Now, let's just grant that all the people in these organizations definitely know things about finance
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and Mormonism and cigarettes and AI that you might not know because they are insiders and you are not.
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They have access to information and experiences that you do not have.
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And that might even make it a little bit difficult for you to win an argument with them.
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But arguing with their belief, trying to figure out whether or not its truth value is true or false, is not the only way to take a skeptical attitude towards it.
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We could also ask, what work is the belief doing for them?
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What does the thing that they believe allow the organization they're a part of to do
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that it wouldn't be able to do if the people in the organization didn't believe that thing?
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And this started to become clearer to me
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when I started listening to the actual claims that Jacob Coxon was making because a lot of them don't really add up.
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Like, here's what he actually said on Anderson Cooper.
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It's easiest to understand it if you think about real things that happened two months ago, OpenAI agents, AIs, hacked into third-party infrastructure entirely at their own accord.
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And this was like a concentrated hacking spree that they carried out of their own volition.
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And I think that if you extrapolate into the future the level of capabilities of these AIs with the same independent volition, they could cause extreme havoc.
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For example, hacking critical infrastructure, building extinction-level bioweapons.
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Only on Tuesday, OpenAI solved a Millennium problem, one of the biggest unsolved open problems in mathematics, purely autonomously using an AI.
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So the idea that AI can build an extinction-level bioweapon is kind of ridiculous.
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Like, here's a thread from David Bellamy, one of the few AI researchers who's actually worked in bioscience, explaining why that's, in his words, bogus.
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Because basically, in order for the AI to engineer a deadly virus,
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some humans would have to build a $100 million bio lab that is both capable of being controlled entirely via AI, which has, you know, cold storage and,
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like, cell culture rooms, all of which is API-driven, and which is specifically supplied with the base materials of deadly viruses at scale.
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And, you know, we could all just, um, not do that, right?
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We could just choose not to build the lab.
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In fact, if we were to build such a lab, would it be accurate to say that the AI designed the bioweapon?
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Or would you say that we, the humans, designed the bioweapon by creating the exact, like, necessary conditions for it to happen?
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Then there's the idea that the AI solved a millennium math problem, and yeah, OpenAI did announce that they did this, but then a few days later,
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the mathematician, who was already working on the problem and was about to solve it, said that OpenAI had heard a rumor he was about to solve it, stole the approach he came up with,
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fed it into their AI, and then spent $20 million worth of computation on solving it before he could.
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Now, OpenAI denied this, and the story is pretty complicated, But at a minimum, OpenAI was not truthful when it said that the AI solved the problem all by itself.
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The truth was, they got help through normal human channels.
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The human channels of rumors and stealing.
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And they did not disclose that.
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And finally, there's the idea that a swarm of AIs hacked another company entirely of their own volition.
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So this is the example that freaked people out the most, and it's the one that people throw in my face the most when I express any skepticism about existential risk.
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Adam, didn't you hear?
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You know, the agents are hacking all by themselves!
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Well, we need to ask, like, is this story real?
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And yes, I mean, it did happen, but the question is, how do we frame what happened?
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Because OpenAI framed it as that they gave a swarm of chatbots a hacking problem to solve, but that in order to solve it,
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the chatbots independently decided to hack into another company's servers to see if the answer was there, and that they first hacked into a bunch of insecure message boards
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so they could talk amongst themselves in order to do so.
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And yeah, that sounds like pretty smart behavior, pretty unpredictable behavior.
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But, you know, my friends Ed Zitron and Cory Doctorow have both covered this story, Ed on his wonderful podcast and Cory on his wonderful blog.
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And they explain it much better than I do, so I'll put the links down below.
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But the short version is, if you look into the details of what actually happened in this story, you can frame it quite differently.
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Because what they actually did was they hooked up Python script to an LLM
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that was trained on a database of specifically years of real-life hackers who were completing real-life hacking challenges.
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The database was composed of their code and also the conversations between the hackers
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and you know what those hackers did in that code and in those conversations?
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They hacked into their competitors to see if they had the answers and they conspired about doing so on insecure message boards.
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You know why they did that?
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Because they were trying to complete hacking challenges.
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So it's not surprising that an AI trained almost exclusively on that data set ended up hacking in that particular way.
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In fact, that was entirely predictable.
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It should have been predicted by the people at OpenAI.
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Why the fuck were they acting surprised?
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They basically set up a hacking machine, pressed go, walked away for the weekend, and came back on Monday saying, We're all trying to find the guy who did this.
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So if you look at all the public statements of the companies, the CEOs, Jacob Coxon together, There's a clear pattern where they declare
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that the AI did something on its own
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when really they were the ones who did it They were the droids they're looking for.
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You are Pagliacci motherfuckers.
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The risk, the danger is never their actions The risk is always the thing the AI did
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and if you inflate
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that idea as large as possible you get Existential risk you get the idea
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that the AI is eventually going to do something so dangerous It's going to wipe out all of humanity.
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And what work does that belief do for them?
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Well, it absolves them of any responsibility for their actions now.
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It allows them to justify anything they do.
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Because if they genuinely believe that AI is an existential risk, and they believe that it's going to be built no matter what,
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and they believe that they're the only ones who really understand the existential risk, then that means that they must be the ones to build AI,
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and anything that they do to advance that goal is therefore worthwhile.
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In other words, by focusing on this largely hypothetical existential threat,
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they are able to ignore all the bad shit that they are currently doing right now.
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They're able to ignore the fact that the data centers they're building are using so much energy, they're basically reversing a generation's worth of progress on climate change,
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which is a real threat that is currently killing people around the world.
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They're ignoring the fact
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that their product is currently being used by bosses to fire
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employees in order to put in place an AI system that demonstrably cannot do their jobs yet.
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And they're able to ignore the fact that their technology is currently being used to kill civilians in Gaza.
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That is not science fiction.
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That is a threat right now and you'll notice that Jacob Coxon didn't talk about that threat.
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You'll notice that Dario Amade doesn't talk about that threat.
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Why aren't they going on Anderson Cooper and talking about that shit?
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Because if they acknowledge that those risks, those current harms that they are causing,
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were as or more important than their made up 10% risk of extinction in the next decade, well then they wouldn't be able to build AI anymore.
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Or at least they wouldn't be able to build it with a clear conscience.
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It is difficult to get a man to understand something, when his salary depends on his not understanding it.
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In fact, what if his salary depended on the lack of understanding so much, that he had to make sure the rest of us didn't understand it either.
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Because for the last year, we the public have been pretty upset about AI, right?
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But we've been upset about the real harms it's been causing.
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We've been upset about getting fired from our jobs, we've been upset about the data center in our backyard, about the water, about climate change, about our electricity bills going up.
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And as a result, the public really thinks AI bad, right?
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But what if AI was not bad in a way that we could put our finger on?
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What if AI was bad in a hypothetical way?
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Now, because of the existential threat risk, AI bad is getting a little bit confused, isn't it?
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Like, is AI bad because of the data center?
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Or is AI bad because it's going to wipe out all of humanity?
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Which one is the bigger risk?
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Well, there's no way to say.
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Maybe we need to be worried about China building AI before us.
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Maybe the only way to forestall the bad things about AI is to build AI even faster.
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Who's to say?
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And, you know, if the public is confused, if the public can't make up its mind, well then, the people on the inside, the people in the industry,
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the people who all believe that they know what the risk really is, well then, they get to call the shots, don't they?
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Whether it is true or not, and whether it is genuine or not, the belief within the AI community
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that AI represents an existential threat works to push the public's worries about AI into things that are unprovable and hypothetical
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in order to distract us from the current harms the industry is causing.
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That is the work that this belief does for them.
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And as a result, we should be skeptical of it.
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And you know what the most ironic thing is?
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Is that there's
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so many people who have been trying to raise the alarm about the real concrete harms
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that this industry is doing to the world that we live in today.
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There's thinkers like Timny Gebru and Emily Bender who have been calling bullshit on this industry from the beginning.
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There's reporters like Karen Howe.
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There's the average people who show up to their city council meetings to protest at data center.
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There are so many people who are worried about the real harms.
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But those people's tweets don't get 150 million views on X.
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Those people don't get invited onto Anderson Cooper nearly as often
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as the insiders who can tell us what all the people inside the industry believe.
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But you know, when everybody in a group believes
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that the work they are doing has some unmeasurable chance of bringing about the end of the world
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and that's why their precious work cannot be interrupted, that doesn't sound like a company at all.
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That sounds like a cult.
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And you know, if you're dealing with a cult, if you want to know the truth about the things they believe, you don't start by asking the people inside the cult.
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You don't start by asking them, hey, is it true that we're all gonna die unless we do as you say?
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No, you start by listening really, really hard to the actual critics on the outside.
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คำศัพท์และข้อสังเกตด้านการพูดสำหรับบทเรียนนี้
บทเรียนฝึกพูดระดับ B2 นี้ใช้วิดีโอ “"AI Existential Risk" Was Invented to Distract Us” เป็นสื่อ วิดีโอนี้มี 162 ประโยค และ 2554 คำ สำหรับฝึกพูดตาม ช่วงที่มีเสียงพูดยาว 13:21 ผู้พูดพูดเร็ว ประมาณ 191 คำต่อนาที จึงมีการเชื่อมเสียงและลดเสียงค่อนข้างมาก 84% ของคำอยู่ใน 3,000 คำที่ใช้บ่อยที่สุดในภาษาอังกฤษ ส่วนที่เหลือควรดูไว้ก่อนเริ่มฝึก จากทั้งหมด 162 ประโยค มี 31 ประโยคเป็นคำถาม จึงเหมาะสำหรับฝึกน้ำเสียงประโยคคำถามและการตอบสั้น ๆ
คำศัพท์สำคัญในวิดีโอนี้
คำที่ยากที่สุด 15 คำในวิดีโอ พร้อมคำอ่านและความหมาย:
| คำศัพท์ | คำอ่าน | ความหมาย |
|---|---|---|
| extinction คำนาม | /ɪkˈstɪŋkʃən/ | การสูญพันธุ์ |
| depend คำกริยา | /dɪˈpɛnd/ | พึ่ง |
| volition คำนาม | /voʊˈlɪʃ(ə)n/ | สัญเจตนา, ความจงใจ |
| millennium คำนาม | /mɪˈlɛnɪəm/ | สหัสวรรษ |
| rumor คำนาม | /ˈɹumɚ/ | ข่าวลือ |
| wipe คำกริยา | /waɪp/ | เช็ด |
| cigarette คำนาม | /ˈsɪɡəɹɛt/ | ยาสูบ, บุหรี่ |
| mathematics คำนาม | /mæθ(.ə)ˈmæt.ɪks/ | คณิตศาสตร์ |
| inflate คำกริยา | /ɪnˈfleɪt/ | ขยาย |
| mathematician คำนาม | /ˌmæθ.(ə.)məˈtɪʃ.ən/ | นักคณิตศาสตร์ |
| thinker คำนาม | /ˈθɪŋ.kɚ/ | นักคิด |
| disclose คำกริยา | /dɪsˈkləʊz/ | เปิดเผย, แพร่งพราย |
| calculate คำกริยา | /ˈkælkjʊleɪt/ | คำนวณ |
| backyard คำนาม | /bækˈjɑːd/ | สวนหลังบ้าน |
| researcher คำนาม | /ˈɹiˌsɝ.t͡ʃɚ/ | นักวิจัย |
ประโยคที่ควรฝึกพูดซ้ำ
ประโยคสั้น ๆ ที่สมบูรณ์จากวิดีโอ ซึ่งนำไปใช้ในบทสนทนาประจำวันได้:
- We could also ask, what work is the belief doing for them?
- Adam, didn't you hear?
- You know why they did that?
ไวยากรณ์ในวิดีโอนี้
โครงสร้างที่ผู้พูดใช้บ่อยที่สุด พร้อมคำพูดจริงจากวิดีโอ:
| โครงสร้าง | ในวิดีโอ |
|---|---|
| Present perfect continuous have/has been + -ing — การกระทำที่เริ่มก่อนหน้านี้และยังดำเนินอยู่ | has been saying · it's been causing · have been trying |
| Relative clauses who / which + อนุประโยค — ข้อมูลเพิ่มเติมเกี่ยวกับคนหรือสิ่งของ | people who come · everyone who worked · guy who did |
| Passive voice be + กริยาช่อง 3 — เน้นสิ่งที่เกิดขึ้น ไม่ใช่ผู้กระทำ | being controlled · is specifically supplied · was trained |
| Present perfect have/has + กริยาช่อง 3 — เหตุการณ์ในอดีตที่ยังเกี่ยวข้องกับปัจจุบัน | has led · have been · we've been |
การออกเสียงที่ควรระวัง
ผู้พูดใช้รูปย่อและรูปลดเสียง 41 ครั้ง เช่น they're, don't, didn't ให้พูดแบบสั้นตามที่ได้ยิน
- เสียง “th”: hypothetical /ˌhaɪpəˈθɛtɪkəl/, mathematics /mæθ(.ə)ˈmæt.ɪks/, mathematician /ˌmæθ.(ə.)məˈtɪʃ.ən/, thinker /ˈθɪŋ.kɚ/, truthful /ˈtɹuːθ.f(ə)l/
- เสียง “sh” และ “zh”: existential /ˌɛɡzɪˈstɛnʃl̩/, extinction /ɪkˈstɪŋkʃən/, volition /voʊˈlɪʃ(ə)n/, computation /ˌkɑmpjʊˈteɪʃn̩/, mathematician /ˌmæθ.(ə.)məˈtɪʃ.ən/
- คำยาว — ลงเสียงหนักให้ถูกพยางค์: bioweapon /ˈbaɪ.oʊˌwɛ.pən/, hypothetical /ˌhaɪpəˈθɛtɪkəl/, mathematics /mæθ(.ə)ˈmæt.ɪks/, demonstrably /diˈmɑnstrəbli/, extrapolate /ɛkˈstɹæp.əˌleɪt/
เสียงที่คนไทยมักออกเสียงยาก:
- เสียงท้ายคำ — ออกเสียงให้ครบ ไม่เปลี่ยนเป็นตัวสะกดแบบไทย: hypothetical /ˌhaɪpəˈθɛtɪkəl/, skeptical /ˈskɛptɪkəl/, mathematics /mæθ(.ə)ˈmæt.ɪks/, acknowledge /əkˈnɑ.lɪd͡ʒ/, absolve /æbˈzɑlv/
- /v/ — ไม่ใช่ /w/ ให้ฟันบนแตะริมฝีปากล่าง: volition /voʊˈlɪʃ(ə)n/, absolve /æbˈzɑlv/, unsolved /ʌnˈsɑlvd/, havoc /ˈhævək/, civilians /sɪˈvɪl.jənz/
- /z/ — เสียงก้อง ไม่ใช่ /s/: existential /ˌɛɡzɪˈstɛnʃl̩/, absolve /æbˈzɑlv/, compose /kəmˈpəʊz/, skepticism /ˈskɛp.tɪˌsɪ.zəm/, disclose /dɪsˈkləʊz/
วิธีฝึกกับวิดีโอนี้
- ฟังวิดีโอให้จบหนึ่งรอบโดยยังไม่ต้องพูด แล้วจดคำที่ยังไม่รู้จัก
- เริ่มที่ความเร็ว 0.75× พูดตามทีละประโยค แล้วกลับไปใช้ความเร็วปกติเมื่อเริ่มคล่อง
- อัดเสียงตัวเองแล้วเทียบกับต้นฉบับ โดยสังเกตคำอย่าง extinction, depend, volition เป็นพิเศษ
เทคนิค Shadowing คืออะไร?
Shadowing เป็นเทคนิคการเรียนรู้ภาษาที่ได้รับการรับรองทางวิทยาศาสตร์ พัฒนาขึ้นสำหรับการฝึกนักแปลมืออาชีพ วิธีการนี้เรียบง่ายแต่ทรงพลัง: คุณฟังเสียงภาษาอังกฤษจากเจ้าของภาษาและพูดตามทันที — เหมือนเงาที่ตามผู้พูดด้วยช่วงเวลาห่าง 1-2 วินาที การวิจัยแสดงว่าเทคนิคนี้ปรับปรุงความแม่นยำในการออกเสียง ทำนองเสียง จังหวะ การเชื่อมเสียง การฟังเข้าใจ และความคล่องแคล่วในการพูดได้อย่างมีนัยสำคัญ